{"uid":"cap_6ie5Ke2Re8pSr_DaIKFFX","slug":"brand-mention-inventories-record-quality-audit-iqr-outlier-flags-2b98f9c4","name":"Brand Mention Inventories — Record Quality Audit + IQR Outlier Flags","description":"Brand mention inventories — Record quality audit + IQR outlier flags: Record quality audit + IQR outlier flags for supplied brand mention inventories records (mention_count, source_count). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-company-18-014?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","mention_count","source_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"mention_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_count":1,"company_group":"group-a","mention_count":10},{"date":"2026-10-02","row_id":"row-2","source_count":2,"company_group":"group-b","mention_count":20},{"date":"2026-10-03","row_id":"row-3","source_count":3,"company_group":"group-a","mention_count":15},{"date":"2026-10-04","row_id":"row-4","source_count":4,"company_group":"group-b","mention_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["mention_count","source_count"],"type":"string","default":"mention_count"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_Uz7qEpTfcE_6i2N39IAyj","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Audits record quality and flags IQR-based outliers in brand mention inventory data (mention_count and source_count) for up to 200 rows, producing two independent analytical reports.","exampleAgentPrompt":"Can you audit these brand mention inventory records for quality issues and flag any IQR outliers in the mention_count field? I have 4 rows: row-1 for group-a on 2026-10-01 with mention_count 10 and source_count 1, row-2 for group-b on 2026-10-02 with mention_count 20 and source_count 2, row-3 for group-a on 2026-10-03 with mention_count 15 and source_count 3, and row-4 for group-b on 2026-10-04 with mention_count 30 and source_count 4.","exampleUseCases":[{"title":"Weekly brand monitoring data quality check","prompt":"Run a quality audit and IQR outlier check on my weekly brand mention data — I have 50 rows with row_id, company_group, date, mention_count, and source_count, and I want to know which records have quality issues or anomalous mention_count values."},{"title":"Competitive brand mention anomaly detection","prompt":"I'm comparing brand mentions across three company groups over the past month and I need you to flag any rows where the source_count looks like an IQR outlier — can you audit this set of 120 brand mention inventory records and give me two reports?"},{"title":"Pre-analysis data cleansing for brand mentions","prompt":"Before I run my analysis, can you check these 80 brand mention inventory rows for record quality problems and flag outliers in both mention_count and source_count using IQR? I want to know which rows to drop or investigate further."}],"resultDescription":"Returns two independent analytical reports: (1) a record quality audit identifying data issues such as missing values, malformed dates, or out-of-range entries across the supplied rows, and (2) IQR-based outlier flags identifying which rows have statistically anomalous mention_count or source_count values, all computed locally without external lookups.","failureModes":["Fewer than 1 or more than 200 rows causes validation failure","Missing required fields (row_id, company_group, date, mention_count, source_count) causes rejection","Invalid date format (not YYYY-MM-DD) triggers schema error","field enum value not 'mention_count' or 'source_count' causes error","Null values in numeric fields may limit IQR computation","Payment of 0.01 USDC not completed blocks execution"],"whenToPreferThis":"Choose this endpoint when you have brand mention inventory data (up to 200 rows) and need both a record quality audit and IQR outlier detection in a single call for a flat $0.01 USDC fee. It is ideal for pre-processing pipelines where you want to identify bad or anomalous records before downstream analysis, and when you need two distinct reports (quality + outliers) without setting up a local analytics environment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T18:57:17.952Z","isFirstParty":false,"canonicalSlug":"brand-mention-inventories-record-quality-audit-iqr-outlier-flags-2b98f9c4"}